Overview

Dataset statistics

Number of variables14
Number of observations26064
Missing cells16272
Missing cells (%)4.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 MiB
Average record size in memory112.0 B

Variable types

DateTime1
Numeric13

Alerts

Power (kW) is highly overall correlated with Rear bearing temperature (°C) and 6 other fieldsHigh correlation
Wind direction (°) is highly overall correlated with Nacelle position (°)High correlation
Nacelle position (°) is highly overall correlated with Wind direction (°)High correlation
blade_angle is highly overall correlated with Rear bearing temperature (°C)High correlation
Rear bearing temperature (°C) is highly overall correlated with Power (kW) and 7 other fieldsHigh correlation
Rotor speed (RPM) is highly overall correlated with Power (kW) and 6 other fieldsHigh correlation
Generator RPM (RPM) is highly overall correlated with Power (kW) and 6 other fieldsHigh correlation
Nacelle ambient temperature (°C) is highly overall correlated with Metal particle count counterHigh correlation
Front bearing temperature (°C) is highly overall correlated with Power (kW) and 6 other fieldsHigh correlation
Tower Acceleration X (mm/ss) is highly overall correlated with Power (kW) and 6 other fieldsHigh correlation
Wind speed (m/s) is highly overall correlated with Power (kW) and 6 other fieldsHigh correlation
Tower Acceleration y (mm/ss) is highly overall correlated with Power (kW) and 6 other fieldsHigh correlation
Metal particle count counter is highly overall correlated with Nacelle ambient temperature (°C)High correlation
blade_angle has 2262 (8.7%) missing valuesMissing
Rear bearing temperature (°C) has 2262 (8.7%) missing valuesMissing
Nacelle ambient temperature (°C) has 2262 (8.7%) missing valuesMissing
Front bearing temperature (°C) has 2262 (8.7%) missing valuesMissing
Tower Acceleration X (mm/ss) has 2262 (8.7%) missing valuesMissing
Tower Acceleration y (mm/ss) has 2262 (8.7%) missing valuesMissing
Metal particle count counter has 2262 (8.7%) missing valuesMissing
# Date and time has unique valuesUnique
blade_angle has 9126 (35.0%) zerosZeros
Rotor speed (RPM) has 1328 (5.1%) zerosZeros

Reproduction

Analysis started2023-07-08 12:01:11.365909
Analysis finished2023-07-08 12:01:27.366076
Duration16 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

# Date and time
Date

Distinct26064
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size203.8 KiB
Minimum2021-01-01 00:00:00
Maximum2021-06-30 23:50:00
2023-07-08T17:31:27.530854image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:27.625611image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Power (kW)
Real number (ℝ)

Distinct25850
Distinct (%)99.5%
Missing73
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean551.5227
Minimum-15.305518
Maximum2077.291
Zeros1
Zeros (%)< 0.1%
Negative4097
Negative (%)15.7%
Memory size203.8 KiB
2023-07-08T17:31:27.728843image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-15.305518
5-th percentile-2.3092548
Q162.059671
median265.71903
Q3827.35101
95-th percentile2009.0963
Maximum2077.291
Range2092.5965
Interquartile range (IQR)765.29134

Descriptive statistics

Standard deviation644.38681
Coefficient of variation (CV)1.1683777
Kurtosis0.10829725
Mean551.5227
Median Absolute Deviation (MAD)266.39231
Skewness1.1975283
Sum14334626
Variance415234.36
MonotonicityNot monotonic
2023-07-08T17:31:27.820848image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-1.860000014 5
 
< 0.1%
-1.820000052 5
 
< 0.1%
-2.029999971 5
 
< 0.1%
-0.7099999785 5
 
< 0.1%
-1.070000052 5
 
< 0.1%
-1.809999943 4
 
< 0.1%
-1.879999995 4
 
< 0.1%
-1.210000038 4
 
< 0.1%
-1.539999962 3
 
< 0.1%
-1.100000024 3
 
< 0.1%
Other values (25840) 25948
99.6%
(Missing) 73
 
0.3%
ValueCountFrequency (%)
-15.3055181 1
< 0.1%
-15.25317047 1
< 0.1%
-14.62641006 1
< 0.1%
-14.60502142 1
< 0.1%
-14.05664801 1
< 0.1%
-13.57409949 1
< 0.1%
-13.39280095 1
< 0.1%
-13.30700213 1
< 0.1%
-13.15876467 1
< 0.1%
-12.97940907 1
< 0.1%
ValueCountFrequency (%)
2077.290991 1
< 0.1%
2074.358219 1
< 0.1%
2073.043512 1
< 0.1%
2072.454305 1
< 0.1%
2070.297375 1
< 0.1%
2069.173279 1
< 0.1%
2068.603955 1
< 0.1%
2068.172894 1
< 0.1%
2067.687909 1
< 0.1%
2067.203973 1
< 0.1%

Wind direction (°)
Real number (ℝ)

Distinct25798
Distinct (%)99.3%
Missing73
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean177.31875
Minimum0.039999999
Maximum359.91115
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size203.8 KiB
2023-07-08T17:31:27.915498image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.039999999
5-th percentile15.782781
Q168.250673
median196.97956
Q3260.67924
95-th percentile332.29283
Maximum359.91115
Range359.87115
Interquartile range (IQR)192.42856

Descriptive statistics

Standard deviation104.31365
Coefficient of variation (CV)0.58828325
Kurtosis-1.2550029
Mean177.31875
Median Absolute Deviation (MAD)85.933065
Skewness-0.16864113
Sum4608691.5
Variance10881.337
MonotonicityNot monotonic
2023-07-08T17:31:28.010620image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.56000137 4
 
< 0.1%
9.510000229 4
 
< 0.1%
267.3900146 3
 
< 0.1%
28 3
 
< 0.1%
32.04000092 3
 
< 0.1%
40.41999817 3
 
< 0.1%
25.48999977 3
 
< 0.1%
19.23999977 3
 
< 0.1%
35.70999908 3
 
< 0.1%
34 3
 
< 0.1%
Other values (25788) 25959
99.6%
(Missing) 73
 
0.3%
ValueCountFrequency (%)
0.03999999911 1
< 0.1%
0.06516634791 1
< 0.1%
0.0700000003 1
< 0.1%
0.09052092682 1
< 0.1%
0.1098320344 1
< 0.1%
0.1168998765 1
< 0.1%
0.1402478906 1
< 0.1%
0.1561105202 1
< 0.1%
0.1566804801 1
< 0.1%
0.1668714264 1
< 0.1%
ValueCountFrequency (%)
359.9111461 1
< 0.1%
359.9066988 1
< 0.1%
359.8963457 1
< 0.1%
359.8693191 1
< 0.1%
359.8046533 1
< 0.1%
359.7837483 1
< 0.1%
359.7635942 1
< 0.1%
359.75 1
< 0.1%
359.7426169 1
< 0.1%
359.7268914 1
< 0.1%

Nacelle position (°)
Real number (ℝ)

Distinct6480
Distinct (%)24.9%
Missing73
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean177.71396
Minimum0.29401308
Maximum359.91373
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size203.8 KiB
2023-07-08T17:31:28.114521image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.29401308
5-th percentile17.293486
Q169.336849
median198.3916
Q3258.75711
95-th percentile334.48853
Maximum359.91373
Range359.61972
Interquartile range (IQR)189.42026

Descriptive statistics

Standard deviation104.67938
Coefficient of variation (CV)0.58903298
Kurtosis-1.2531324
Mean177.71396
Median Absolute Deviation (MAD)85.60994
Skewness-0.15766658
Sum4618963.6
Variance10957.774
MonotonicityNot monotonic
2023-07-08T17:31:28.209941image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
253.2692871 308
 
1.2%
199.4886169 139
 
0.5%
254.3663025 137
 
0.5%
204.9769897 134
 
0.5%
249.976593 110
 
0.4%
249.9760437 105
 
0.4%
33.75689697 95
 
0.4%
276.3186951 94
 
0.4%
192.9037781 93
 
0.4%
190.7086487 91
 
0.3%
Other values (6470) 24685
94.7%
ValueCountFrequency (%)
0.2940130798 1
 
< 0.1%
0.3464464836 1
 
< 0.1%
0.4199999869 1
 
< 0.1%
0.5059249587 1
 
< 0.1%
0.5593559801 1
 
< 0.1%
0.7767380322 1
 
< 0.1%
0.8250595011 1
 
< 0.1%
0.8299999833 3
< 0.1%
0.8306274414 4
< 0.1%
0.8306291103 2
< 0.1%
ValueCountFrequency (%)
359.9137348 1
 
< 0.1%
359.8200073 1
 
< 0.1%
359.8099976 1
 
< 0.1%
359.7410569 1
 
< 0.1%
359.7336073 1
 
< 0.1%
359.7330627 5
 
< 0.1%
359.7325134 52
0.2%
359.730011 54
0.2%
359.6900024 1
 
< 0.1%
359.6393739 1
 
< 0.1%

blade_angle
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct8975
Distinct (%)37.7%
Missing2262
Missing (%)8.7%
Infinite0
Infinite (%)0.0%
Mean9.409113
Minimum0
Maximum92.493332
Zeros9126
Zeros (%)35.0%
Negative0
Negative (%)0.0%
Memory size203.8 KiB
2023-07-08T17:31:28.312900image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.19188889
Q33.7425417
95-th percentile44.990002
Maximum92.493332
Range92.493332
Interquartile range (IQR)3.7425417

Descriptive statistics

Standard deviation20.637049
Coefficient of variation (CV)2.1933044
Kurtosis5.6667952
Mean9.409113
Median Absolute Deviation (MAD)0.19188889
Skewness2.4933141
Sum223955.71
Variance425.88778
MonotonicityNot monotonic
2023-07-08T17:31:28.406901image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9126
35.0%
44.99000168 2052
 
7.9%
89.98999786 461
 
1.8%
0.02450000048 379
 
1.5%
62.07666675 283
 
1.1%
1.49000001 266
 
1.0%
0.04900000095 190
 
0.7%
0.07350000143 96
 
0.4%
0.09800000191 87
 
0.3%
92.48999786 53
 
0.2%
Other values (8965) 10809
41.5%
(Missing) 2262
 
8.7%
ValueCountFrequency (%)
0 9126
35.0%
0.0001666666629 13
 
< 0.1%
0.000185185181 1
 
< 0.1%
0.0003333333259 10
 
< 0.1%
0.0003421052555 1
 
< 0.1%
0.0004999999888 9
 
< 0.1%
0.0004999999888 1
 
< 0.1%
0.0006666666518 1
 
< 0.1%
0.0006666666518 2
 
< 0.1%
0.0007407407242 1
 
< 0.1%
ValueCountFrequency (%)
92.49333191 2
 
< 0.1%
92.49316521 1
 
< 0.1%
92.4929985 1
 
< 0.1%
92.49133148 1
 
< 0.1%
92.49016457 1
 
< 0.1%
92.48999786 2
 
< 0.1%
92.48999786 53
0.2%
92.4644989 1
 
< 0.1%
92.45999908 1
 
< 0.1%
92.43466466 1
 
< 0.1%

Rear bearing temperature (°C)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct20946
Distinct (%)88.0%
Missing2262
Missing (%)8.7%
Infinite0
Infinite (%)0.0%
Mean58.939739
Minimum9.4150002
Maximum72.845001
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size203.8 KiB
2023-07-08T17:31:28.503354image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum9.4150002
5-th percentile30.1
Q155.585461
median63.991071
Q367.41
95-th percentile70.052625
Maximum72.845001
Range63.430001
Interquartile range (IQR)11.824539

Descriptive statistics

Standard deviation12.734296
Coefficient of variation (CV)0.21605619
Kurtosis2.8857802
Mean58.939739
Median Absolute Deviation (MAD)4.4414276
Skewness-1.7937451
Sum1402883.7
Variance162.16228
MonotonicityNot monotonic
2023-07-08T17:31:28.595617image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11.30000019 14
 
0.1%
11.39999962 8
 
< 0.1%
15.39999962 7
 
< 0.1%
11.5 6
 
< 0.1%
12.10000038 6
 
< 0.1%
13.10000038 6
 
< 0.1%
67.46499977 6
 
< 0.1%
67.91749954 5
 
< 0.1%
66.59749985 5
 
< 0.1%
67.7775013 5
 
< 0.1%
Other values (20936) 23734
91.1%
(Missing) 2262
 
8.7%
ValueCountFrequency (%)
9.415000153 1
< 0.1%
9.470000029 1
< 0.1%
9.534210657 1
< 0.1%
9.584210848 1
< 0.1%
9.600000381 1
< 0.1%
9.63000021 1
< 0.1%
9.645000124 1
< 0.1%
9.675000095 1
< 0.1%
9.689999866 1
< 0.1%
9.692499828 1
< 0.1%
ValueCountFrequency (%)
72.84500084 1
< 0.1%
72.78000031 1
< 0.1%
72.59249992 1
< 0.1%
72.5125 1
< 0.1%
72.44999962 1
< 0.1%
72.4375 1
< 0.1%
72.4224987 1
< 0.1%
72.39000015 1
< 0.1%
72.38999977 1
< 0.1%
72.34750023 1
< 0.1%

Rotor speed (RPM)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23224
Distinct (%)89.4%
Missing73
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean9.5249922
Minimum0
Maximum15.302099
Zeros1328
Zeros (%)5.1%
Negative0
Negative (%)0.0%
Memory size203.8 KiB
2023-07-08T17:31:28.695232image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q18.1448252
median9.5748795
Q313.351557
95-th percentile15.159414
Maximum15.302099
Range15.302099
Interquartile range (IQR)5.2067321

Descriptive statistics

Standard deviation4.5579344
Coefficient of variation (CV)0.47852369
Kurtosis-0.19169071
Mean9.5249922
Median Absolute Deviation (MAD)2.3327411
Skewness-0.74675533
Sum247564.07
Variance20.774766
MonotonicityNot monotonic
2023-07-08T17:31:28.791400image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1328
 
5.1%
8.140000343 238
 
0.9%
8.149999619 30
 
0.1%
8.159999847 20
 
0.1%
8.170000076 15
 
0.1%
8.180000305 14
 
0.1%
8.25 12
 
< 0.1%
8.199999809 12
 
< 0.1%
8.289999962 11
 
< 0.1%
8.569999695 10
 
< 0.1%
Other values (23214) 24301
93.2%
(Missing) 73
 
0.3%
ValueCountFrequency (%)
0 1328
5.1%
0.0005250001122 1
 
< 0.1%
0.00765600102 1
 
< 0.1%
0.009100002469 1
 
< 0.1%
0.009999999776 1
 
< 0.1%
0.01050000242 5
 
< 0.1%
0.0110000018 2
 
< 0.1%
0.01105263413 1
 
< 0.1%
0.0113710016 1
 
< 0.1%
0.01150000188 8
 
< 0.1%
ValueCountFrequency (%)
15.30209886 1
< 0.1%
15.2950792 1
< 0.1%
15.29461403 1
< 0.1%
15.28674509 1
< 0.1%
15.28515396 1
< 0.1%
15.27895318 1
< 0.1%
15.27808432 1
< 0.1%
15.27799997 1
< 0.1%
15.27682395 1
< 0.1%
15.2731951 1
< 0.1%

Generator RPM (RPM)
Real number (ℝ)

Distinct25753
Distinct (%)99.1%
Missing73
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean1130.6541
Minimum-36.721024
Maximum1813.5188
Zeros18
Zeros (%)0.1%
Negative1
Negative (%)< 0.1%
Memory size203.8 KiB
2023-07-08T17:31:28.894354image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-36.721024
5-th percentile3.037118
Q1967.93982
median1137.6504
Q31583.5177
95-th percentile1797.1474
Maximum1813.5188
Range1850.2398
Interquartile range (IQR)615.57789

Descriptive statistics

Standard deviation540.0226
Coefficient of variation (CV)0.47761964
Kurtosis-0.18610839
Mean1130.6541
Median Absolute Deviation (MAD)276.7999
Skewness-0.7517801
Sum29386830
Variance291624.41
MonotonicityNot monotonic
2023-07-08T17:31:28.988926image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 18
 
0.1%
969.9699707 12
 
< 0.1%
970 10
 
< 0.1%
969.9199829 9
 
< 0.1%
969.9000244 9
 
< 0.1%
970.0599976 8
 
< 0.1%
969.960022 8
 
< 0.1%
970.0900269 8
 
< 0.1%
970.0200195 8
 
< 0.1%
969.9799805 8
 
< 0.1%
Other values (25743) 25893
99.3%
(Missing) 73
 
0.3%
ValueCountFrequency (%)
-36.72102374 1
 
< 0.1%
0 18
0.1%
0.009999999776 4
 
< 0.1%
0.01999999955 1
 
< 0.1%
0.02999999933 2
 
< 0.1%
0.07999999821 1
 
< 0.1%
0.09000000358 1
 
< 0.1%
0.1000000015 1
 
< 0.1%
0.1599999964 1
 
< 0.1%
0.5099999905 1
 
< 0.1%
ValueCountFrequency (%)
1813.51878 1
< 0.1%
1809.92771 1
< 0.1%
1809.677519 1
< 0.1%
1809.66853 1
< 0.1%
1809.603624 1
< 0.1%
1809.44129 1
< 0.1%
1808.975967 1
< 0.1%
1808.918564 1
< 0.1%
1808.89789 1
< 0.1%
1808.724094 1
< 0.1%

Nacelle ambient temperature (°C)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct19853
Distinct (%)83.4%
Missing2262
Missing (%)8.7%
Infinite0
Infinite (%)0.0%
Mean7.6917686
Minimum-3.9100001
Maximum26.815
Zeros0
Zeros (%)0.0%
Negative1431
Negative (%)5.5%
Memory size203.8 KiB
2023-07-08T17:31:29.087743image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-3.9100001
5-th percentile-0.26000001
Q13.83
median7.1774998
Q310.5825
95-th percentile18.674875
Maximum26.815
Range30.725
Interquartile range (IQR)6.7525001

Descriptive statistics

Standard deviation5.4821091
Coefficient of variation (CV)0.71272413
Kurtosis0.1359225
Mean7.6917686
Median Absolute Deviation (MAD)3.3695831
Skewness0.59599082
Sum183079.48
Variance30.05352
MonotonicityNot monotonic
2023-07-08T17:31:29.180340image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 25
 
0.1%
1.200000048 20
 
0.1%
1 17
 
0.1%
5.994999981 13
 
< 0.1%
3.700000048 13
 
< 0.1%
2.799999952 12
 
< 0.1%
3 12
 
< 0.1%
5.699999809 12
 
< 0.1%
8.484999943 11
 
< 0.1%
8.5 11
 
< 0.1%
Other values (19843) 23656
90.8%
(Missing) 2262
 
8.7%
ValueCountFrequency (%)
-3.910000086 1
< 0.1%
-3.902631659 1
< 0.1%
-3.844999981 1
< 0.1%
-3.842499995 1
< 0.1%
-3.804999948 1
< 0.1%
-3.799999952 1
< 0.1%
-3.787499964 1
< 0.1%
-3.782499969 1
< 0.1%
-3.769999981 1
< 0.1%
-3.767499983 1
< 0.1%
ValueCountFrequency (%)
26.81499996 1
< 0.1%
26.47500019 1
< 0.1%
26.32000017 1
< 0.1%
26.32000017 1
< 0.1%
26.03000011 1
< 0.1%
25.81000013 1
< 0.1%
25.72250013 1
< 0.1%
25.70499992 1
< 0.1%
25.7000001 1
< 0.1%
25.675 1
< 0.1%

Front bearing temperature (°C)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct20731
Distinct (%)87.1%
Missing2262
Missing (%)8.7%
Infinite0
Infinite (%)0.0%
Mean61.162453
Minimum10.4
Maximum81.1825
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size203.8 KiB
2023-07-08T17:31:29.399236image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum10.4
5-th percentile31.450375
Q154.625329
median66.345
Q371.814375
95-th percentile73.902499
Maximum81.1825
Range70.7825
Interquartile range (IQR)17.189046

Descriptive statistics

Standard deviation14.059841
Coefficient of variation (CV)0.22987701
Kurtosis1.4056891
Mean61.162453
Median Absolute Deviation (MAD)6.4396871
Skewness-1.380275
Sum1455788.7
Variance197.67914
MonotonicityNot monotonic
2023-07-08T17:31:29.494875image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13.19999981 13
 
< 0.1%
13.60000038 8
 
< 0.1%
71.23999939 7
 
< 0.1%
13.5 6
 
< 0.1%
11.10000038 6
 
< 0.1%
12 6
 
< 0.1%
18.29999924 6
 
< 0.1%
73.57249985 6
 
< 0.1%
18.20000076 6
 
< 0.1%
10.60000038 6
 
< 0.1%
Other values (20721) 23732
91.1%
(Missing) 2262
 
8.7%
ValueCountFrequency (%)
10.39999962 1
 
< 0.1%
10.43499975 1
 
< 0.1%
10.5250001 1
 
< 0.1%
10.53000011 1
 
< 0.1%
10.55500021 1
 
< 0.1%
10.60000038 6
< 0.1%
10.60750031 1
 
< 0.1%
10.66999998 1
 
< 0.1%
10.6974998 1
 
< 0.1%
10.69999981 4
< 0.1%
ValueCountFrequency (%)
81.18249969 1
< 0.1%
80.80000191 1
< 0.1%
80.74499969 1
< 0.1%
80.73000145 1
< 0.1%
80.63499908 1
< 0.1%
80.57249947 1
< 0.1%
80.56749916 1
< 0.1%
80.5650013 1
< 0.1%
80.54750061 1
< 0.1%
80.53249969 1
< 0.1%

Tower Acceleration X (mm/ss)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct23802
Distinct (%)100.0%
Missing2262
Missing (%)8.7%
Infinite0
Infinite (%)0.0%
Mean52.369077
Minimum2.626515
Maximum214.46329
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size203.8 KiB
2023-07-08T17:31:29.600972image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum2.626515
5-th percentile4.150635
Q129.211101
median48.731943
Q374.778521
95-th percentile109.79324
Maximum214.46329
Range211.83678
Interquartile range (IQR)45.56742

Descriptive statistics

Standard deviation32.498888
Coefficient of variation (CV)0.62057401
Kurtosis-0.21631608
Mean52.369077
Median Absolute Deviation (MAD)22.251716
Skewness0.46764133
Sum1246488.8
Variance1056.1777
MonotonicityNot monotonic
2023-07-08T17:31:29.693817image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.63336041 1
 
< 0.1%
32.61687562 1
 
< 0.1%
53.96835785 1
 
< 0.1%
50.53920779 1
 
< 0.1%
41.67428184 1
 
< 0.1%
40.44719253 1
 
< 0.1%
38.71795275 1
 
< 0.1%
38.58143253 1
 
< 0.1%
49.67901173 1
 
< 0.1%
43.6068666 1
 
< 0.1%
Other values (23792) 23792
91.3%
(Missing) 2262
 
8.7%
ValueCountFrequency (%)
2.626515025 1
< 0.1%
2.720084763 1
< 0.1%
2.832100347 1
< 0.1%
2.858062398 1
< 0.1%
2.893791789 1
< 0.1%
2.93046658 1
< 0.1%
2.976701903 1
< 0.1%
2.988630408 1
< 0.1%
3.010270163 1
< 0.1%
3.015181869 1
< 0.1%
ValueCountFrequency (%)
214.4632948 1
< 0.1%
200.2258833 1
< 0.1%
191.5197901 1
< 0.1%
190.5738178 1
< 0.1%
182.6369396 1
< 0.1%
181.805534 1
< 0.1%
180.3751157 1
< 0.1%
179.4555279 1
< 0.1%
177.2206066 1
< 0.1%
176.96073 1
< 0.1%

Wind speed (m/s)
Real number (ℝ)

Distinct24546
Distinct (%)94.4%
Missing73
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean5.8031878
Minimum0.12986292
Maximum22.151195
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size203.8 KiB
2023-07-08T17:31:29.789939image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.12986292
5-th percentile2.0142965
Q13.7119871
median5.2798872
Q37.3834175
95-th percentile11.403721
Maximum22.151195
Range22.021332
Interquartile range (IQR)3.6714304

Descriptive statistics

Standard deviation2.8727526
Coefficient of variation (CV)0.4950301
Kurtosis0.62102793
Mean5.8031878
Median Absolute Deviation (MAD)1.7747791
Skewness0.84269254
Sum150830.65
Variance8.2527075
MonotonicityNot monotonic
2023-07-08T17:31:29.880953image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.599999905 11
 
< 0.1%
5.630000114 10
 
< 0.1%
4.199999809 9
 
< 0.1%
5.28000021 9
 
< 0.1%
4.909999847 9
 
< 0.1%
2.670000076 9
 
< 0.1%
4.409999847 9
 
< 0.1%
6.730000019 8
 
< 0.1%
5.449999809 8
 
< 0.1%
4.960000038 8
 
< 0.1%
Other values (24536) 25901
99.4%
(Missing) 73
 
0.3%
ValueCountFrequency (%)
0.1298629189 1
< 0.1%
0.1893378168 1
< 0.1%
0.2135250166 1
< 0.1%
0.2473500688 1
< 0.1%
0.2561064709 1
< 0.1%
0.25987509 1
< 0.1%
0.2898377664 1
< 0.1%
0.2988940597 1
< 0.1%
0.3011624865 1
< 0.1%
0.3144376591 1
< 0.1%
ValueCountFrequency (%)
22.15119505 1
< 0.1%
20.97752533 1
< 0.1%
20.86605759 1
< 0.1%
20.33832564 1
< 0.1%
20.16105361 1
< 0.1%
19.89226894 1
< 0.1%
19.78537683 1
< 0.1%
19.5888649 1
< 0.1%
19.47146084 1
< 0.1%
19.24220624 1
< 0.1%

Tower Acceleration y (mm/ss)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct23802
Distinct (%)100.0%
Missing2262
Missing (%)8.7%
Infinite0
Infinite (%)0.0%
Mean26.170916
Minimum2.7534846
Maximum214.10945
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size203.8 KiB
2023-07-08T17:31:29.977129image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum2.7534846
5-th percentile4.271197
Q114.86277
median23.065544
Q334.313549
95-th percentile57.970337
Maximum214.10945
Range211.35597
Interquartile range (IQR)19.450779

Descriptive statistics

Standard deviation16.709728
Coefficient of variation (CV)0.63848463
Kurtosis4.3260325
Mean26.170916
Median Absolute Deviation (MAD)9.4287596
Skewness1.4053168
Sum622920.15
Variance279.21501
MonotonicityNot monotonic
2023-07-08T17:31:30.070673image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.898877764 1
 
< 0.1%
25.84777248 1
 
< 0.1%
25.67600467 1
 
< 0.1%
27.19841542 1
 
< 0.1%
20.59202049 1
 
< 0.1%
19.71599562 1
 
< 0.1%
19.36513031 1
 
< 0.1%
17.1147084 1
 
< 0.1%
20.72050986 1
 
< 0.1%
22.61556907 1
 
< 0.1%
Other values (23792) 23792
91.3%
(Missing) 2262
 
8.7%
ValueCountFrequency (%)
2.753484571 1
< 0.1%
2.912063769 1
< 0.1%
3.00858596 1
< 0.1%
3.008585978 1
< 0.1%
3.041284198 1
< 0.1%
3.061380172 1
< 0.1%
3.094106448 1
< 0.1%
3.123043552 1
< 0.1%
3.1273497 1
< 0.1%
3.140445212 1
< 0.1%
ValueCountFrequency (%)
214.1094549 1
< 0.1%
180.3917339 1
< 0.1%
177.0505728 1
< 0.1%
161.6267387 1
< 0.1%
154.2301689 1
< 0.1%
153.5531353 1
< 0.1%
152.6764606 1
< 0.1%
145.4473957 1
< 0.1%
144.6834942 1
< 0.1%
142.9109755 1
< 0.1%

Metal particle count counter
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct16
Distinct (%)0.1%
Missing2262
Missing (%)8.7%
Infinite0
Infinite (%)0.0%
Mean538.42429
Minimum530
Maximum548
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size203.8 KiB
2023-07-08T17:31:30.152009image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum530
5-th percentile532
Q1533
median541
Q3542
95-th percentile546
Maximum548
Range18
Interquartile range (IQR)9

Descriptive statistics

Standard deviation5.1524553
Coefficient of variation (CV)0.0095695074
Kurtosis-1.4485155
Mean538.42429
Median Absolute Deviation (MAD)5
Skewness0.0032598919
Sum12815575
Variance26.547795
MonotonicityIncreasing
2023-07-08T17:31:30.228008image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
541 7259
27.9%
532 5319
20.4%
546 2722
 
10.4%
534 2215
 
8.5%
543 2165
 
8.3%
533 1764
 
6.8%
537 651
 
2.5%
547 585
 
2.2%
536 450
 
1.7%
542 428
 
1.6%
Other values (6) 244
 
0.9%
(Missing) 2262
 
8.7%
ValueCountFrequency (%)
530 102
 
0.4%
531 3
 
< 0.1%
532 5319
20.4%
533 1764
 
6.8%
534 2215
 
8.5%
535 41
 
0.2%
536 450
 
1.7%
537 651
 
2.5%
540 4
 
< 0.1%
541 7259
27.9%
ValueCountFrequency (%)
548 61
 
0.2%
547 585
 
2.2%
546 2722
 
10.4%
545 33
 
0.1%
543 2165
 
8.3%
542 428
 
1.6%
541 7259
27.9%
540 4
 
< 0.1%
537 651
 
2.5%
536 450
 
1.7%

Interactions

2023-07-08T17:31:25.649694image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:12.106002image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:13.245205image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:14.370556image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:15.488231image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:16.542366image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:17.758865image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:18.894546image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:20.010863image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:21.230217image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:22.355618image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:23.416504image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:24.583450image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:25.733320image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:12.181314image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:13.328225image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:14.451354image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:15.563649image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:16.620691image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:17.840523image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:18.974700image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:20.090962image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:21.311387image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:22.430968image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:23.492791image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:24.658726image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:25.826044image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:12.264296image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:13.414149image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:14.538622image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:15.646069image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:16.826352image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:17.930051image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:19.063282image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:20.178190image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:21.401918image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:22.516538image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:23.577061image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:24.744655image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:25.918441image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:12.348250image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:13.505774image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:14.626590image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:15.733254image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:16.912094image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:18.020610image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:19.152795image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:20.381549image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:21.491441image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:22.599942image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:23.660524image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:24.829450image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:26.000041image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:12.422109image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:13.584745image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:14.705425image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:15.810228image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:16.990128image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:18.101008image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:19.232418image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:20.457616image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:21.572734image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:22.675615image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:23.736772image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:24.906363image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:26.090475image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:12.505329image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:13.676056image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:14.793831image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:15.893359image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:17.073565image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:18.190724image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:19.321587image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:20.543267image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:21.659583image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:22.760607image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:23.818524image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:24.989782image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:26.183647image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:12.590878image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:13.768483image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:14.884788image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:15.978827image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:17.164644image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:18.282499image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:19.412599image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:20.632831image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:21.752064image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:22.847163image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:23.906394image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:25.076745image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:26.275665image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:12.673960image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:13.859786image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:14.974269image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:16.061341image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:17.251506image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:18.373997image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:19.501317image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:20.721471image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:21.841728image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:22.932801image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:23.989635image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:25.163235image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:26.364377image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:12.845572image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:13.946925image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:15.060894image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:16.144458image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:17.338940image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:18.462048image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:19.588189image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:20.807374image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:21.928551image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:23.014394image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:24.070579image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:25.245352image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:26.457944image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:12.930847image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:14.036854image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:15.152619image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:16.228272image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:17.426520image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:18.553903image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:19.679599image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:20.898117image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:22.018063image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:23.101182image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:24.268070image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:25.333584image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:26.540431image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:13.007397image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:14.117055image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:15.233407image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:16.305187image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:17.508322image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:18.635818image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:19.759825image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:20.977480image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:22.099475image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:23.176178image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:24.343714image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:25.409543image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:26.623653image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:13.082533image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:14.197581image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:15.315167image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:16.380258image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:17.587631image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:18.716645image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:19.840342image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:21.058191image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:22.181916image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:23.251977image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:24.418618image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:25.487483image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:26.706145image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:13.160345image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:14.280881image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:15.394844image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:16.454928image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:17.668856image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:18.803108image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:19.920748image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:21.138105image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:22.262736image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:23.329529image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:24.496219image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:31:25.563008image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Correlations

2023-07-08T17:31:30.308269image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Power (kW)Wind direction (°)Nacelle position (°)blade_angleRear bearing temperature (°C)Rotor speed (RPM)Generator RPM (RPM)Nacelle ambient temperature (°C)Front bearing temperature (°C)Tower Acceleration X (mm/ss)Wind speed (m/s)Tower Acceleration y (mm/ss)Metal particle count counter
Power (kW)1.000-0.057-0.049-0.3930.8290.9880.987-0.1180.9240.6240.9090.770-0.203
Wind direction (°)-0.0571.0000.8560.020-0.019-0.056-0.0580.096-0.0310.206-0.0250.1600.074
Nacelle position (°)-0.0490.8561.0000.013-0.012-0.048-0.0500.087-0.0260.199-0.0300.1510.054
blade_angle-0.3930.0200.0131.000-0.571-0.400-0.4010.163-0.467-0.225-0.251-0.1710.039
Rear bearing temperature (°C)0.829-0.019-0.012-0.5711.0000.8330.831-0.0030.9180.5050.7210.597-0.034
Rotor speed (RPM)0.988-0.056-0.048-0.4000.8331.0000.999-0.1090.9270.6320.8920.768-0.197
Generator RPM (RPM)0.987-0.058-0.050-0.4010.8310.9991.000-0.1200.9270.6300.8910.766-0.204
Nacelle ambient temperature (°C)-0.1180.0960.0870.163-0.003-0.109-0.1201.000-0.1030.015-0.124-0.0360.687
Front bearing temperature (°C)0.924-0.031-0.026-0.4670.9180.9270.927-0.1031.0000.5660.8220.700-0.141
Tower Acceleration X (mm/ss)0.6240.2060.199-0.2250.5050.6320.6300.0150.5661.0000.5080.860-0.102
Wind speed (m/s)0.909-0.025-0.030-0.2510.7210.8920.891-0.1240.8220.5081.0000.744-0.222
Tower Acceleration y (mm/ss)0.7700.1600.151-0.1710.5970.7680.766-0.0360.7000.8600.7441.000-0.152
Metal particle count counter-0.2030.0740.0540.039-0.034-0.197-0.2040.687-0.141-0.102-0.222-0.1521.000

Missing values

2023-07-08T17:31:26.836940image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
A simple visualization of nullity by column.
2023-07-08T17:31:27.021622image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-07-08T17:31:27.219829image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

# Date and timePower (kW)Wind direction (°)Nacelle position (°)blade_angleRear bearing temperature (°C)Rotor speed (RPM)Generator RPM (RPM)Nacelle ambient temperature (°C)Front bearing temperature (°C)Tower Acceleration X (mm/ss)Wind speed (m/s)Tower Acceleration y (mm/ss)Metal particle count counter
02021-01-01 00:00:00-4.431785298.784569310.34210289.98999814.4600000.0000000.6152590.96000017.2025014.6333602.2694816.898878530.0
12021-01-01 00:10:00-2.451966297.088993310.34210289.98999814.4800000.0000000.6909010.56000017.1075005.7128762.4423758.291622530.0
22021-01-01 00:20:00-2.592277293.547889310.34210289.98999814.3175000.0000001.9163190.01000017.1000006.7406353.2012258.023160530.0
32021-01-01 00:30:00-3.383991298.670732310.34210289.98999814.3175000.0000002.313140-0.48250017.0000006.4442473.1120699.925518530.0
42021-01-01 00:40:00-2.399150288.808822310.34210289.98999814.3400000.0000001.571156-0.50250016.9000006.6303323.9014068.080585530.0
52021-01-01 00:50:00-2.999340283.026852309.80645389.98999814.1625000.0000001.627926-0.45750016.81249910.7462555.1384199.673251530.0
62021-01-01 01:00:00-4.406710288.471010280.85049889.98999814.0166670.0150001.033760-0.33333316.7000017.5600574.6818129.159661530.0
72021-01-01 01:10:00-1.980352300.087168280.70785589.98999813.9700000.0000002.542371-0.19500016.5000005.6092803.3964507.140647530.0
82021-01-01 01:20:00-2.801942296.806834280.70785589.98999813.8875000.0158783.398553-0.40000016.5200008.8158583.5640196.773277530.0
92021-01-01 01:30:00-3.408531304.856204280.70785589.98999813.8325000.0115004.003253-0.30000016.4250006.5331362.8202256.733731530.0
# Date and timePower (kW)Wind direction (°)Nacelle position (°)blade_angleRear bearing temperature (°C)Rotor speed (RPM)Generator RPM (RPM)Nacelle ambient temperature (°C)Front bearing temperature (°C)Tower Acceleration X (mm/ss)Wind speed (m/s)Tower Acceleration y (mm/ss)Metal particle count counter
260542021-06-30 22:20:0022.70000123.52000019.490000NaNNaN8.14970.080017NaNNaNNaN3.28NaNNaN
260552021-06-30 22:30:0011.91000022.09000019.490000NaNNaN8.14969.880005NaNNaNNaN3.02NaNNaN
260562021-06-30 22:40:00-4.65000025.73000019.490000NaNNaN8.14970.020020NaNNaNNaN2.70NaNNaN
260572021-06-30 22:50:00-6.86000026.34000019.490000NaNNaN4.03479.480011NaNNaNNaN2.37NaNNaN
260582021-06-30 23:00:005.50000039.45000119.860001NaNNaN2.45293.359985NaNNaNNaN3.09NaNNaN
260592021-06-30 23:10:0076.69000229.68000032.660000NaNNaN8.14970.090027NaNNaNNaN3.85NaNNaN
260602021-06-30 23:20:00112.70999929.62999932.660000NaNNaN8.14970.020020NaNNaNNaN4.21NaNNaN
260612021-06-30 23:30:0091.54000127.91000032.660000NaNNaN8.14969.969971NaNNaNNaN4.21NaNNaN
260622021-06-30 23:40:0053.13999924.79000132.660000NaNNaN8.14969.809998NaNNaNNaN3.83NaNNaN
260632021-06-30 23:50:004.61000028.13999932.660000NaNNaN8.14970.000000NaNNaNNaN2.82NaNNaN